Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = './data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [2]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[2]:
<matplotlib.image.AxesImage at 0x7fc94b201198>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[3]:
<matplotlib.image.AxesImage at 0x7fc94b12ad68>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.2.1
Default GPU Device: /gpu:0

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    real_input_image = tf.placeholder(
        tf.float32, [None, image_width, image_height, image_channels])
    z_input_image = tf.placeholder(tf.float32, [None, z_dim])
    learning_rate = tf.placeholder(tf.float32)
    return real_input_image, z_input_image, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
ERROR:tensorflow:==================================
Object was never used (type <class 'tensorflow.python.framework.ops.Operation'>):
<tf.Operation 'assert_rank_2/Assert/Assert' type=Assert>
If you want to mark it as used call its "mark_used()" method.
It was originally created here:
['File "/home/carnd/anaconda3/envs/dl/lib/python3.5/runpy.py", line 184, in _run_module_as_main\n    "__main__", mod_spec)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/runpy.py", line 85, in _run_code\n    exec(code, run_globals)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/__main__.py", line 3, in <module>\n    app.launch_new_instance()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance\n    app.start()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 474, in start\n    ioloop.IOLoop.instance().start()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 177, in start\n    super(ZMQIOLoop, self).start()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tornado/ioloop.py", line 887, in start\n    handler_func(fd_obj, events)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events\n    self._handle_recv()', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv\n    self._run_callback(callback, msg)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback\n    callback(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher\n    return self.dispatch_shell(stream, msg)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell\n    handler(stream, idents, msg)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 390, in execute_request\n    user_expressions, allow_stdin)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute\n    res = shell.run_cell(code, store_history=store_history, silent=silent)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 501, in run_cell\n    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell\n    interactivity=interactivity, compiler=compiler, result=result)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2827, in run_ast_nodes\n    if self.run_code(code, result):', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)', 'File "<ipython-input-5-38424e90053c>", line 22, in <module>\n    tests.test_model_inputs(model_inputs)', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 12, in func_wrapper\n    result = func(*args)', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 68, in test_model_inputs\n    _check_input(learn_rate, [], \'Learning Rate\')', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 34, in _check_input\n    _assert_tensor_shape(tensor, shape, \'Real Input\')', 'File "/home/carnd/deep-learning/face_generation/problem_unittests.py", line 20, in _assert_tensor_shape\n    assert tf.assert_rank(tensor, len(shape), message=\'{} has wrong rank\'.format(display_name))', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py", line 617, in assert_rank\n    dynamic_condition, data, summarize)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py", line 571, in _assert_rank_condition\n    return control_flow_ops.Assert(condition, data, summarize=summarize)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py", line 170, in wrapped\n    return _add_should_use_warning(fn(*args, **kwargs))', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py", line 139, in _add_should_use_warning\n    wrapped = TFShouldUseWarningWrapper(x)', 'File "/home/carnd/anaconda3/envs/dl/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py", line 96, in __init__\n    stack = [s.strip() for s in traceback.format_stack()]']
==================================
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [6]:
def discriminator(images, reuse=False, alpha=0.2, keep_prob=None):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    def conv2d(x, filters):
        return tf.layers.conv2d(x, filters, kernel_size=5, strides=2, padding='same',
                                kernel_initializer=tf.contrib.layers.xavier_initializer())

    def leakyLeRU(x):
        return tf.maximum(x * alpha, x)

    with tf.variable_scope('discriminator', reuse=reuse):
        x = conv2d(images, 64)
        x = leakyLeRU(x)

        x = conv2d(x, 128)
        x = tf.layers.batch_normalization(x, training=True)
        x = leakyLeRU(x)

        x = conv2d(x, 256)
        x = tf.layers.batch_normalization(x, training=True)
        x = leakyLeRU(x)
        if keep_prob != None:
            x = tf.nn.dropout(x, keep_prob)

        flat = tf.reshape(x, (-1, 4*4*256))
        logits = tf.layers.dense(flat, 1)


        out = tf.sigmoid(logits)

    return out, logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [7]:
def generator(z, out_channel_dim, is_train=True, alpha=0.2, keep_prob=None):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    def conv2d_transpose(x, filters, strides):
        return tf.layers.conv2d_transpose(x, filters, kernel_size=5, strides=strides, padding='same')

    def leakyLeRU(x):
        return tf.maximum(alpha * x, x)

    reuse = not is_train
    with tf.variable_scope('generator', reuse=reuse):
        x = tf.layers.dense(z, 7 * 7 * 512)
        x = tf.reshape(x, (-1, 7, 7, 512))
        x = tf.layers.batch_normalization(x, training=is_train)
        x = leakyLeRU(x)

        x = conv2d_transpose(x, 256, 2)
        x = tf.layers.batch_normalization(x, training=is_train)
        x = leakyLeRU(x)

        x = conv2d_transpose(x, 128, 2)
        x = tf.layers.batch_normalization(x, training=is_train)
        x = leakyLeRU(x)

        x = conv2d_transpose(x, 64, 1)
        x = tf.layers.batch_normalization(x, training=is_train)
        x = leakyLeRU(x)
        if keep_prob != None:
             x = tf.nn.dropout(x, keep_prob)

        logits = conv2d_transpose(x, out_channel_dim, 1)


        out = tf.tanh(logits)

    return out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [8]:
def model_loss(input_real, input_z, out_channel_dim, alpha=0.2, g_keep_prob=None, d_keep_prob=None):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    g_model = generator(
        input_z, out_channel_dim, alpha=alpha, keep_prob=g_keep_prob)
    d_model_real, d_logits_real = discriminator(
        input_real, reuse=False, alpha=alpha, keep_prob=d_keep_prob)
    d_model_fake, d_logits_fake = discriminator(
        g_model, reuse=True, alpha=alpha, keep_prob=d_keep_prob)

    # Discriminator real loss. Labels are 1 since the discriminator attempts to detect
    # real images.
    # One-sided label smoothing (https://github.com/soumith/ganhacks#6-use-soft-and-noisy-labels)
    labels = tf.ones_like(d_model_real) * 0.9
    d_loss_real = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
            logits=d_logits_real, labels=labels))

    # Discriminator fake loss. Labels are 0 since the discriminator attempts to detect
    # fake images.
    d_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
            logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))

    d_loss = d_loss_real + d_loss_fake

    # Generator loss. Labels are 1 since the generator attempts to fake
    # the discriminator.
    labels = tf.ones_like(d_model_fake)
    g_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
            logits=d_logits_fake, labels=labels))

    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [9]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]

    update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
    with tf.control_dependencies(update_ops):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(
            d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(
            g_loss, var_list=g_vars)

    return d_train_opt, g_train_opt

"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [10]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode, g_keep_prob, d_keep_prob):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z, g_keep_prob: 1.0, d_keep_prob: 1.0})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [11]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode,
         g_keep_prob, d_keep_prob):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    image_width = data_shape[1]
    image_height = data_shape[2]
    image_channels = data_shape[3]
    real_input_image, z_input_image, learning_rate_pf = model_inputs(
        image_width, image_height, image_channels, z_dim)

    g_keep_prob_pf = tf.placeholder(tf.float32)
    d_keep_prob_pf = tf.placeholder(tf.float32)

    d_loss, g_loss = model_loss(
        real_input_image, z_input_image, image_channels, alpha=0.2,
        g_keep_prob=g_keep_prob_pf, d_keep_prob=d_keep_prob_pf)
    d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate_pf, beta1)

    losses = []
    steps = 0
    print_every = 10
    show_every = 50

    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for orig_batch_images in get_batches(batch_size):
                steps += 1

                # Convert the scale of input images [-0.5, 0.5] to [-1, 1]         
                batch_images = orig_batch_images * 2.0

                # Sample random noise for G
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))

                # Try normal distribution as discussed in 
                # https://github.com/soumith/ganhacks
                # batch_z = np.clip(np.random.normal(0, 0.1, size=(batch_size, z_dim)), -1.0, 1.0)

                # Run optimizers
                _ = sess.run(d_opt, feed_dict={
                        real_input_image: batch_images,
                        z_input_image:    batch_z,
                        learning_rate_pf: learning_rate,
                        g_keep_prob_pf:   g_keep_prob,
                        d_keep_prob_pf:   d_keep_prob})

                # Run g_opt twice to make sure that d_loss does not go to zero
                # http://bamos.github.io/2016/08/09/deep-completion/                
                #
                # NOTE: CHANGE SUGGESTED BY REVIEWER.
                for i in range(2):
                    _ = sess.run(g_opt, feed_dict={
                            real_input_image: batch_images,
                            z_input_image: batch_z,
                            learning_rate_pf: learning_rate,
                            g_keep_prob_pf: g_keep_prob,
                            d_keep_prob_pf: d_keep_prob})

                if steps % print_every == 0:
                    # At the end of each epoch, get the losses and print them out
                    train_loss_d = d_loss.eval({
                        real_input_image: batch_images,
                        z_input_image: batch_z,
                        g_keep_prob_pf: g_keep_prob,
                        d_keep_prob_pf: d_keep_prob})
                    train_loss_g = g_loss.eval({
                        real_input_image: batch_images,
                        z_input_image: batch_z,
                        g_keep_prob_pf: g_keep_prob,
                        d_keep_prob_pf: d_keep_prob})

                    print("Epoch {}/{}...".format(epoch_i + 1, epoch_count),
                          "Discriminator Loss: {:.4f}...".format(train_loss_d),
                          "Generator Loss: {:.4f}".format(train_loss_g))
                    losses.append((train_loss_d, train_loss_g))

                if steps % show_every == 0:
                    show_generator_output(sess, 64, z_input_image, image_channels, data_image_mode, g_keep_prob_pf, d_keep_prob_pf)

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [15]:
beta1 = 0.5
z_dim = 100

batch_size = 32
learning_rate = 0.0002

g_keep_prob = 0.6
d_keep_prob = 0.9

tf.reset_default_graph()


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode, g_keep_prob, d_keep_prob)
Epoch 1/2... Discriminator Loss: 0.4672... Generator Loss: 2.6170
Epoch 1/2... Discriminator Loss: 0.3894... Generator Loss: 3.3720
Epoch 1/2... Discriminator Loss: 2.9463... Generator Loss: 1.4860
Epoch 1/2... Discriminator Loss: 1.9109... Generator Loss: 0.8597
Epoch 1/2... Discriminator Loss: 1.8293... Generator Loss: 0.6296
Epoch 1/2... Discriminator Loss: 2.2038... Generator Loss: 0.3506
Epoch 1/2... Discriminator Loss: 1.9298... Generator Loss: 0.5041
Epoch 1/2... Discriminator Loss: 1.6497... Generator Loss: 0.6860
Epoch 1/2... Discriminator Loss: 1.5142... Generator Loss: 0.9552
Epoch 1/2... Discriminator Loss: 1.5862... Generator Loss: 1.0269
Epoch 1/2... Discriminator Loss: 1.8570... Generator Loss: 0.4393
Epoch 1/2... Discriminator Loss: 1.6567... Generator Loss: 0.6154
Epoch 1/2... Discriminator Loss: 1.6338... Generator Loss: 0.5582
Epoch 1/2... Discriminator Loss: 1.6695... Generator Loss: 0.5654
Epoch 1/2... Discriminator Loss: 1.8048... Generator Loss: 0.4869
Epoch 1/2... Discriminator Loss: 1.3674... Generator Loss: 1.0121
Epoch 1/2... Discriminator Loss: 1.5047... Generator Loss: 0.5441
Epoch 1/2... Discriminator Loss: 1.8622... Generator Loss: 0.4382
Epoch 1/2... Discriminator Loss: 1.6641... Generator Loss: 0.4187
Epoch 1/2... Discriminator Loss: 1.3457... Generator Loss: 0.6995
Epoch 1/2... Discriminator Loss: 1.4950... Generator Loss: 0.9876
Epoch 1/2... Discriminator Loss: 1.5148... Generator Loss: 0.6320
Epoch 1/2... Discriminator Loss: 1.9035... Generator Loss: 0.2765
Epoch 1/2... Discriminator Loss: 1.4690... Generator Loss: 0.8125
Epoch 1/2... Discriminator Loss: 1.6461... Generator Loss: 0.9975
Epoch 1/2... Discriminator Loss: 1.6105... Generator Loss: 0.4908
Epoch 1/2... Discriminator Loss: 1.6642... Generator Loss: 0.4995
Epoch 1/2... Discriminator Loss: 1.5711... Generator Loss: 0.6070
Epoch 1/2... Discriminator Loss: 1.4814... Generator Loss: 0.4836
Epoch 1/2... Discriminator Loss: 1.6722... Generator Loss: 0.5179
Epoch 1/2... Discriminator Loss: 1.5246... Generator Loss: 0.8319
Epoch 1/2... Discriminator Loss: 1.5074... Generator Loss: 0.5535
Epoch 1/2... Discriminator Loss: 1.5327... Generator Loss: 0.6062
Epoch 1/2... Discriminator Loss: 1.5076... Generator Loss: 0.6337
Epoch 1/2... Discriminator Loss: 1.4136... Generator Loss: 0.5877
Epoch 1/2... Discriminator Loss: 1.5498... Generator Loss: 0.9664
Epoch 1/2... Discriminator Loss: 1.5450... Generator Loss: 0.4923
Epoch 1/2... Discriminator Loss: 1.5746... Generator Loss: 0.7592
Epoch 1/2... Discriminator Loss: 1.4808... Generator Loss: 0.6920
Epoch 1/2... Discriminator Loss: 1.6234... Generator Loss: 0.7614
Epoch 1/2... Discriminator Loss: 1.4930... Generator Loss: 0.7423
Epoch 1/2... Discriminator Loss: 1.5226... Generator Loss: 0.6250
Epoch 1/2... Discriminator Loss: 1.5295... Generator Loss: 0.7313
Epoch 1/2... Discriminator Loss: 1.5176... Generator Loss: 0.4733
Epoch 1/2... Discriminator Loss: 1.6523... Generator Loss: 0.4954
Epoch 1/2... Discriminator Loss: 1.5755... Generator Loss: 0.4840
Epoch 1/2... Discriminator Loss: 1.4880... Generator Loss: 0.8578
Epoch 1/2... Discriminator Loss: 1.6470... Generator Loss: 0.3997
Epoch 1/2... Discriminator Loss: 1.4386... Generator Loss: 0.4981
Epoch 1/2... Discriminator Loss: 1.5907... Generator Loss: 0.5197
Epoch 1/2... Discriminator Loss: 1.3003... Generator Loss: 0.8895
Epoch 1/2... Discriminator Loss: 1.3390... Generator Loss: 0.8916
Epoch 1/2... Discriminator Loss: 1.3980... Generator Loss: 0.7392
Epoch 1/2... Discriminator Loss: 1.3678... Generator Loss: 0.8298
Epoch 1/2... Discriminator Loss: 1.5493... Generator Loss: 0.4953
Epoch 1/2... Discriminator Loss: 1.4590... Generator Loss: 0.7013
Epoch 1/2... Discriminator Loss: 1.4441... Generator Loss: 0.7201
Epoch 1/2... Discriminator Loss: 1.5116... Generator Loss: 0.7342
Epoch 1/2... Discriminator Loss: 1.3139... Generator Loss: 0.8366
Epoch 1/2... Discriminator Loss: 1.5003... Generator Loss: 0.4928
Epoch 1/2... Discriminator Loss: 1.3768... Generator Loss: 0.6467
Epoch 1/2... Discriminator Loss: 1.6212... Generator Loss: 0.5443
Epoch 1/2... Discriminator Loss: 1.3961... Generator Loss: 0.6615
Epoch 1/2... Discriminator Loss: 1.6453... Generator Loss: 0.3703
Epoch 1/2... Discriminator Loss: 1.3937... Generator Loss: 0.7255
Epoch 1/2... Discriminator Loss: 1.6782... Generator Loss: 0.4973
Epoch 1/2... Discriminator Loss: 1.5062... Generator Loss: 0.5634
Epoch 1/2... Discriminator Loss: 1.5468... Generator Loss: 0.6406
Epoch 1/2... Discriminator Loss: 1.4965... Generator Loss: 0.6195
Epoch 1/2... Discriminator Loss: 1.3982... Generator Loss: 0.9284
Epoch 1/2... Discriminator Loss: 1.6491... Generator Loss: 0.5967
Epoch 1/2... Discriminator Loss: 1.5390... Generator Loss: 0.6808
Epoch 1/2... Discriminator Loss: 1.4638... Generator Loss: 0.6518
Epoch 1/2... Discriminator Loss: 1.4733... Generator Loss: 0.7068
Epoch 1/2... Discriminator Loss: 1.5587... Generator Loss: 0.6338
Epoch 1/2... Discriminator Loss: 1.5980... Generator Loss: 0.5786
Epoch 1/2... Discriminator Loss: 1.6836... Generator Loss: 0.4424
Epoch 1/2... Discriminator Loss: 1.5110... Generator Loss: 0.5837
Epoch 1/2... Discriminator Loss: 1.4048... Generator Loss: 0.8402
Epoch 1/2... Discriminator Loss: 1.4976... Generator Loss: 0.7034
Epoch 1/2... Discriminator Loss: 1.6489... Generator Loss: 0.6093
Epoch 1/2... Discriminator Loss: 1.3832... Generator Loss: 0.7501
Epoch 1/2... Discriminator Loss: 1.4824... Generator Loss: 0.4763
Epoch 1/2... Discriminator Loss: 1.5934... Generator Loss: 0.5810
Epoch 1/2... Discriminator Loss: 1.4688... Generator Loss: 0.6937
Epoch 1/2... Discriminator Loss: 1.4893... Generator Loss: 0.6653
Epoch 1/2... Discriminator Loss: 1.3646... Generator Loss: 0.8383
Epoch 1/2... Discriminator Loss: 1.5102... Generator Loss: 0.6861
Epoch 1/2... Discriminator Loss: 1.6353... Generator Loss: 0.4521
Epoch 1/2... Discriminator Loss: 1.6440... Generator Loss: 0.4608
Epoch 1/2... Discriminator Loss: 1.6858... Generator Loss: 0.4954
Epoch 1/2... Discriminator Loss: 1.5277... Generator Loss: 0.6401
Epoch 1/2... Discriminator Loss: 1.5336... Generator Loss: 0.7272
Epoch 1/2... Discriminator Loss: 1.3854... Generator Loss: 0.7170
Epoch 1/2... Discriminator Loss: 1.5262... Generator Loss: 0.9216
Epoch 1/2... Discriminator Loss: 1.4664... Generator Loss: 0.8517
Epoch 1/2... Discriminator Loss: 1.4364... Generator Loss: 0.8514
Epoch 1/2... Discriminator Loss: 1.4085... Generator Loss: 0.5450
Epoch 1/2... Discriminator Loss: 1.3052... Generator Loss: 0.7929
Epoch 1/2... Discriminator Loss: 1.4643... Generator Loss: 0.6326
Epoch 1/2... Discriminator Loss: 1.4244... Generator Loss: 0.6435
Epoch 1/2... Discriminator Loss: 1.4294... Generator Loss: 0.7786
Epoch 1/2... Discriminator Loss: 1.7108... Generator Loss: 0.3955
Epoch 1/2... Discriminator Loss: 1.4415... Generator Loss: 0.8053
Epoch 1/2... Discriminator Loss: 1.5062... Generator Loss: 0.7048
Epoch 1/2... Discriminator Loss: 1.4718... Generator Loss: 0.5688
Epoch 1/2... Discriminator Loss: 1.5765... Generator Loss: 0.9416
Epoch 1/2... Discriminator Loss: 1.5997... Generator Loss: 0.4869
Epoch 1/2... Discriminator Loss: 1.4454... Generator Loss: 0.6350
Epoch 1/2... Discriminator Loss: 1.5551... Generator Loss: 0.9451
Epoch 1/2... Discriminator Loss: 1.5630... Generator Loss: 0.6835
Epoch 1/2... Discriminator Loss: 1.4330... Generator Loss: 1.0721
Epoch 1/2... Discriminator Loss: 1.4463... Generator Loss: 0.7474
Epoch 1/2... Discriminator Loss: 1.4745... Generator Loss: 0.6136
Epoch 1/2... Discriminator Loss: 1.5461... Generator Loss: 0.5248
Epoch 1/2... Discriminator Loss: 1.4912... Generator Loss: 0.6327
Epoch 1/2... Discriminator Loss: 1.4883... Generator Loss: 0.6032
Epoch 1/2... Discriminator Loss: 1.5876... Generator Loss: 0.5102
Epoch 1/2... Discriminator Loss: 1.4420... Generator Loss: 0.7181
Epoch 1/2... Discriminator Loss: 1.5362... Generator Loss: 0.5451
Epoch 1/2... Discriminator Loss: 1.4508... Generator Loss: 0.6209
Epoch 1/2... Discriminator Loss: 1.4212... Generator Loss: 0.7107
Epoch 1/2... Discriminator Loss: 1.4565... Generator Loss: 0.6749
Epoch 1/2... Discriminator Loss: 1.5403... Generator Loss: 0.5431
Epoch 1/2... Discriminator Loss: 1.4821... Generator Loss: 0.5753
Epoch 1/2... Discriminator Loss: 1.4794... Generator Loss: 0.5913
Epoch 1/2... Discriminator Loss: 1.2886... Generator Loss: 0.6957
Epoch 1/2... Discriminator Loss: 1.4135... Generator Loss: 0.8224
Epoch 1/2... Discriminator Loss: 1.4331... Generator Loss: 0.5455
Epoch 1/2... Discriminator Loss: 1.3991... Generator Loss: 0.9632
Epoch 1/2... Discriminator Loss: 1.4577... Generator Loss: 0.7037
Epoch 1/2... Discriminator Loss: 1.4223... Generator Loss: 0.6502
Epoch 1/2... Discriminator Loss: 1.4539... Generator Loss: 0.7240
Epoch 1/2... Discriminator Loss: 1.4674... Generator Loss: 0.5130
Epoch 1/2... Discriminator Loss: 1.6120... Generator Loss: 0.5219
Epoch 1/2... Discriminator Loss: 1.7676... Generator Loss: 0.4411
Epoch 1/2... Discriminator Loss: 1.5725... Generator Loss: 0.6525
Epoch 1/2... Discriminator Loss: 1.4093... Generator Loss: 0.6837
Epoch 1/2... Discriminator Loss: 1.6087... Generator Loss: 0.4622
Epoch 1/2... Discriminator Loss: 1.5475... Generator Loss: 0.4149
Epoch 1/2... Discriminator Loss: 1.6960... Generator Loss: 0.4499
Epoch 1/2... Discriminator Loss: 1.3897... Generator Loss: 0.8680
Epoch 1/2... Discriminator Loss: 1.4557... Generator Loss: 0.6512
Epoch 1/2... Discriminator Loss: 1.6299... Generator Loss: 0.3797
Epoch 1/2... Discriminator Loss: 1.5290... Generator Loss: 0.5939
Epoch 1/2... Discriminator Loss: 1.4074... Generator Loss: 0.7117
Epoch 1/2... Discriminator Loss: 1.5801... Generator Loss: 0.4507
Epoch 1/2... Discriminator Loss: 1.5611... Generator Loss: 0.5758
Epoch 1/2... Discriminator Loss: 1.3814... Generator Loss: 0.8797
Epoch 1/2... Discriminator Loss: 1.2531... Generator Loss: 0.9192
Epoch 1/2... Discriminator Loss: 1.5835... Generator Loss: 0.6170
Epoch 1/2... Discriminator Loss: 1.5631... Generator Loss: 0.5176
Epoch 1/2... Discriminator Loss: 1.4906... Generator Loss: 0.7400
Epoch 1/2... Discriminator Loss: 1.3529... Generator Loss: 0.6409
Epoch 1/2... Discriminator Loss: 1.5685... Generator Loss: 0.5868
Epoch 1/2... Discriminator Loss: 1.6713... Generator Loss: 0.5695
Epoch 1/2... Discriminator Loss: 1.3854... Generator Loss: 0.7947
Epoch 1/2... Discriminator Loss: 1.5165... Generator Loss: 0.5528
Epoch 1/2... Discriminator Loss: 1.3374... Generator Loss: 0.6237
Epoch 1/2... Discriminator Loss: 1.3896... Generator Loss: 0.7072
Epoch 1/2... Discriminator Loss: 1.4987... Generator Loss: 0.6091
Epoch 1/2... Discriminator Loss: 1.4106... Generator Loss: 0.6058
Epoch 1/2... Discriminator Loss: 1.5491... Generator Loss: 0.8480
Epoch 1/2... Discriminator Loss: 1.6250... Generator Loss: 0.4661
Epoch 1/2... Discriminator Loss: 1.3093... Generator Loss: 0.7647
Epoch 1/2... Discriminator Loss: 1.4502... Generator Loss: 0.5120
Epoch 1/2... Discriminator Loss: 1.2934... Generator Loss: 0.7592
Epoch 1/2... Discriminator Loss: 1.5844... Generator Loss: 0.5179
Epoch 1/2... Discriminator Loss: 1.5963... Generator Loss: 0.5077
Epoch 1/2... Discriminator Loss: 1.5123... Generator Loss: 0.7462
Epoch 1/2... Discriminator Loss: 1.3428... Generator Loss: 0.6575
Epoch 1/2... Discriminator Loss: 1.3504... Generator Loss: 0.8512
Epoch 1/2... Discriminator Loss: 1.4627... Generator Loss: 0.5152
Epoch 1/2... Discriminator Loss: 1.4825... Generator Loss: 0.5544
Epoch 1/2... Discriminator Loss: 1.3644... Generator Loss: 0.6140
Epoch 1/2... Discriminator Loss: 1.5151... Generator Loss: 0.5491
Epoch 1/2... Discriminator Loss: 1.4395... Generator Loss: 0.5099
Epoch 1/2... Discriminator Loss: 1.3435... Generator Loss: 0.7203
Epoch 1/2... Discriminator Loss: 1.4862... Generator Loss: 0.8959
Epoch 1/2... Discriminator Loss: 1.5483... Generator Loss: 0.5582
Epoch 1/2... Discriminator Loss: 1.5390... Generator Loss: 0.5501
Epoch 1/2... Discriminator Loss: 1.5994... Generator Loss: 0.7370
Epoch 1/2... Discriminator Loss: 1.3386... Generator Loss: 0.6231
Epoch 1/2... Discriminator Loss: 1.3902... Generator Loss: 0.7884
Epoch 1/2... Discriminator Loss: 1.5768... Generator Loss: 0.4602
Epoch 1/2... Discriminator Loss: 1.3860... Generator Loss: 0.6104
Epoch 1/2... Discriminator Loss: 1.3620... Generator Loss: 0.7163
Epoch 2/2... Discriminator Loss: 1.3152... Generator Loss: 0.8437
Epoch 2/2... Discriminator Loss: 1.4619... Generator Loss: 0.6554
Epoch 2/2... Discriminator Loss: 1.2617... Generator Loss: 0.6794
Epoch 2/2... Discriminator Loss: 1.4287... Generator Loss: 0.6351
Epoch 2/2... Discriminator Loss: 1.3371... Generator Loss: 0.7902
Epoch 2/2... Discriminator Loss: 1.6732... Generator Loss: 0.5618
Epoch 2/2... Discriminator Loss: 1.4375... Generator Loss: 0.4574
Epoch 2/2... Discriminator Loss: 1.4769... Generator Loss: 0.4717
Epoch 2/2... Discriminator Loss: 1.3229... Generator Loss: 0.6048
Epoch 2/2... Discriminator Loss: 1.5027... Generator Loss: 0.7345
Epoch 2/2... Discriminator Loss: 1.3919... Generator Loss: 0.7018
Epoch 2/2... Discriminator Loss: 1.3447... Generator Loss: 0.8230
Epoch 2/2... Discriminator Loss: 1.3276... Generator Loss: 0.6251
Epoch 2/2... Discriminator Loss: 1.5585... Generator Loss: 0.4874
Epoch 2/2... Discriminator Loss: 1.2511... Generator Loss: 0.7494
Epoch 2/2... Discriminator Loss: 1.4954... Generator Loss: 0.6581
Epoch 2/2... Discriminator Loss: 1.2706... Generator Loss: 0.6638
Epoch 2/2... Discriminator Loss: 1.2882... Generator Loss: 0.8026
Epoch 2/2... Discriminator Loss: 1.3289... Generator Loss: 0.5325
Epoch 2/2... Discriminator Loss: 1.3102... Generator Loss: 0.7882
Epoch 2/2... Discriminator Loss: 1.2937... Generator Loss: 0.8041
Epoch 2/2... Discriminator Loss: 1.2573... Generator Loss: 0.6959
Epoch 2/2... Discriminator Loss: 1.4355... Generator Loss: 0.8335
Epoch 2/2... Discriminator Loss: 1.3781... Generator Loss: 0.7141
Epoch 2/2... Discriminator Loss: 1.5869... Generator Loss: 0.4831
Epoch 2/2... Discriminator Loss: 1.3954... Generator Loss: 0.6136
Epoch 2/2... Discriminator Loss: 1.1993... Generator Loss: 0.8339
Epoch 2/2... Discriminator Loss: 1.3334... Generator Loss: 0.5503
Epoch 2/2... Discriminator Loss: 1.4712... Generator Loss: 0.6356
Epoch 2/2... Discriminator Loss: 1.4357... Generator Loss: 0.6267
Epoch 2/2... Discriminator Loss: 1.3180... Generator Loss: 0.5849
Epoch 2/2... Discriminator Loss: 1.3826... Generator Loss: 0.5870
Epoch 2/2... Discriminator Loss: 1.5410... Generator Loss: 0.4473
Epoch 2/2... Discriminator Loss: 1.4635... Generator Loss: 0.5499
Epoch 2/2... Discriminator Loss: 1.4380... Generator Loss: 0.9395
Epoch 2/2... Discriminator Loss: 1.4592... Generator Loss: 0.6168
Epoch 2/2... Discriminator Loss: 1.1736... Generator Loss: 0.8457
Epoch 2/2... Discriminator Loss: 1.3303... Generator Loss: 0.6466
Epoch 2/2... Discriminator Loss: 1.3277... Generator Loss: 0.6953
Epoch 2/2... Discriminator Loss: 1.2082... Generator Loss: 0.8917
Epoch 2/2... Discriminator Loss: 1.3909... Generator Loss: 0.5353
Epoch 2/2... Discriminator Loss: 1.2503... Generator Loss: 0.8289
Epoch 2/2... Discriminator Loss: 1.1796... Generator Loss: 0.6938
Epoch 2/2... Discriminator Loss: 1.2679... Generator Loss: 0.7614
Epoch 2/2... Discriminator Loss: 1.4571... Generator Loss: 0.6140
Epoch 2/2... Discriminator Loss: 1.1881... Generator Loss: 0.9372
Epoch 2/2... Discriminator Loss: 1.3750... Generator Loss: 0.9644
Epoch 2/2... Discriminator Loss: 1.2438... Generator Loss: 0.7517
Epoch 2/2... Discriminator Loss: 1.4558... Generator Loss: 0.5273
Epoch 2/2... Discriminator Loss: 1.2894... Generator Loss: 0.6341
Epoch 2/2... Discriminator Loss: 1.3521... Generator Loss: 0.7878
Epoch 2/2... Discriminator Loss: 1.0495... Generator Loss: 1.1199
Epoch 2/2... Discriminator Loss: 1.3915... Generator Loss: 0.6770
Epoch 2/2... Discriminator Loss: 1.5537... Generator Loss: 0.6052
Epoch 2/2... Discriminator Loss: 1.2734... Generator Loss: 0.9150
Epoch 2/2... Discriminator Loss: 1.3141... Generator Loss: 0.7914
Epoch 2/2... Discriminator Loss: 1.3971... Generator Loss: 0.8471
Epoch 2/2... Discriminator Loss: 1.2509... Generator Loss: 0.6363
Epoch 2/2... Discriminator Loss: 1.8110... Generator Loss: 1.3470
Epoch 2/2... Discriminator Loss: 1.2752... Generator Loss: 0.6856
Epoch 2/2... Discriminator Loss: 1.1817... Generator Loss: 0.8173
Epoch 2/2... Discriminator Loss: 1.1961... Generator Loss: 0.8489
Epoch 2/2... Discriminator Loss: 1.1088... Generator Loss: 0.8251
Epoch 2/2... Discriminator Loss: 1.5078... Generator Loss: 0.4995
Epoch 2/2... Discriminator Loss: 1.5871... Generator Loss: 0.4524
Epoch 2/2... Discriminator Loss: 1.3943... Generator Loss: 0.5482
Epoch 2/2... Discriminator Loss: 1.0954... Generator Loss: 0.8186
Epoch 2/2... Discriminator Loss: 1.3625... Generator Loss: 0.7032
Epoch 2/2... Discriminator Loss: 1.1375... Generator Loss: 1.0691
Epoch 2/2... Discriminator Loss: 1.0311... Generator Loss: 0.8465
Epoch 2/2... Discriminator Loss: 1.1219... Generator Loss: 1.0265
Epoch 2/2... Discriminator Loss: 1.7153... Generator Loss: 0.5344
Epoch 2/2... Discriminator Loss: 1.2193... Generator Loss: 0.6828
Epoch 2/2... Discriminator Loss: 1.4638... Generator Loss: 0.6100
Epoch 2/2... Discriminator Loss: 1.1579... Generator Loss: 1.0840
Epoch 2/2... Discriminator Loss: 1.2218... Generator Loss: 0.9795
Epoch 2/2... Discriminator Loss: 1.3645... Generator Loss: 0.8921
Epoch 2/2... Discriminator Loss: 1.0790... Generator Loss: 0.8002
Epoch 2/2... Discriminator Loss: 1.3874... Generator Loss: 0.6240
Epoch 2/2... Discriminator Loss: 1.2647... Generator Loss: 0.6197
Epoch 2/2... Discriminator Loss: 1.3494... Generator Loss: 0.8563
Epoch 2/2... Discriminator Loss: 1.3287... Generator Loss: 0.8473
Epoch 2/2... Discriminator Loss: 1.4378... Generator Loss: 0.5704
Epoch 2/2... Discriminator Loss: 1.3678... Generator Loss: 0.7178
Epoch 2/2... Discriminator Loss: 1.1751... Generator Loss: 0.9875
Epoch 2/2... Discriminator Loss: 1.2678... Generator Loss: 0.8136
Epoch 2/2... Discriminator Loss: 1.3818... Generator Loss: 0.8174
Epoch 2/2... Discriminator Loss: 1.2666... Generator Loss: 0.6444
Epoch 2/2... Discriminator Loss: 1.1574... Generator Loss: 0.9679
Epoch 2/2... Discriminator Loss: 1.2772... Generator Loss: 0.7622
Epoch 2/2... Discriminator Loss: 1.5982... Generator Loss: 0.4122
Epoch 2/2... Discriminator Loss: 1.3195... Generator Loss: 0.7878
Epoch 2/2... Discriminator Loss: 1.2179... Generator Loss: 0.6791
Epoch 2/2... Discriminator Loss: 1.2439... Generator Loss: 0.7243
Epoch 2/2... Discriminator Loss: 1.1965... Generator Loss: 0.8460
Epoch 2/2... Discriminator Loss: 1.6391... Generator Loss: 0.4021
Epoch 2/2... Discriminator Loss: 1.4427... Generator Loss: 0.7592
Epoch 2/2... Discriminator Loss: 1.4643... Generator Loss: 0.7194
Epoch 2/2... Discriminator Loss: 1.3164... Generator Loss: 1.0107
Epoch 2/2... Discriminator Loss: 1.3457... Generator Loss: 1.0373
Epoch 2/2... Discriminator Loss: 1.5041... Generator Loss: 0.5486
Epoch 2/2... Discriminator Loss: 1.1872... Generator Loss: 0.8636
Epoch 2/2... Discriminator Loss: 1.0798... Generator Loss: 0.8681
Epoch 2/2... Discriminator Loss: 1.0790... Generator Loss: 1.0015
Epoch 2/2... Discriminator Loss: 1.0960... Generator Loss: 0.9278
Epoch 2/2... Discriminator Loss: 1.4822... Generator Loss: 0.8024
Epoch 2/2... Discriminator Loss: 1.3274... Generator Loss: 0.8965
Epoch 2/2... Discriminator Loss: 1.4319... Generator Loss: 0.5614
Epoch 2/2... Discriminator Loss: 1.2260... Generator Loss: 0.7459
Epoch 2/2... Discriminator Loss: 1.1808... Generator Loss: 0.9580
Epoch 2/2... Discriminator Loss: 1.2965... Generator Loss: 0.6472
Epoch 2/2... Discriminator Loss: 0.9955... Generator Loss: 0.9947
Epoch 2/2... Discriminator Loss: 1.2668... Generator Loss: 0.9783
Epoch 2/2... Discriminator Loss: 1.2562... Generator Loss: 0.7871
Epoch 2/2... Discriminator Loss: 1.1812... Generator Loss: 0.8150
Epoch 2/2... Discriminator Loss: 1.2956... Generator Loss: 0.9052
Epoch 2/2... Discriminator Loss: 1.6800... Generator Loss: 0.3915
Epoch 2/2... Discriminator Loss: 1.3067... Generator Loss: 0.6154
Epoch 2/2... Discriminator Loss: 1.2152... Generator Loss: 0.6981
Epoch 2/2... Discriminator Loss: 1.4627... Generator Loss: 1.2578
Epoch 2/2... Discriminator Loss: 1.2012... Generator Loss: 1.0427
Epoch 2/2... Discriminator Loss: 1.4316... Generator Loss: 0.5112
Epoch 2/2... Discriminator Loss: 1.4922... Generator Loss: 0.4931
Epoch 2/2... Discriminator Loss: 1.2554... Generator Loss: 0.8828
Epoch 2/2... Discriminator Loss: 1.1737... Generator Loss: 0.7705
Epoch 2/2... Discriminator Loss: 1.0638... Generator Loss: 0.9989
Epoch 2/2... Discriminator Loss: 1.2763... Generator Loss: 0.7266
Epoch 2/2... Discriminator Loss: 1.1220... Generator Loss: 0.7703
Epoch 2/2... Discriminator Loss: 1.1618... Generator Loss: 0.8903
Epoch 2/2... Discriminator Loss: 1.3049... Generator Loss: 0.8205
Epoch 2/2... Discriminator Loss: 1.4002... Generator Loss: 0.5423
Epoch 2/2... Discriminator Loss: 1.7274... Generator Loss: 0.6538
Epoch 2/2... Discriminator Loss: 1.2314... Generator Loss: 0.8661
Epoch 2/2... Discriminator Loss: 1.2051... Generator Loss: 0.8014
Epoch 2/2... Discriminator Loss: 1.3196... Generator Loss: 0.7760
Epoch 2/2... Discriminator Loss: 1.3408... Generator Loss: 0.6944
Epoch 2/2... Discriminator Loss: 1.2895... Generator Loss: 1.2053
Epoch 2/2... Discriminator Loss: 1.2473... Generator Loss: 0.7619
Epoch 2/2... Discriminator Loss: 1.4012... Generator Loss: 0.5223
Epoch 2/2... Discriminator Loss: 1.0627... Generator Loss: 1.0664
Epoch 2/2... Discriminator Loss: 1.0419... Generator Loss: 0.8934
Epoch 2/2... Discriminator Loss: 1.3807... Generator Loss: 0.5516
Epoch 2/2... Discriminator Loss: 1.4932... Generator Loss: 0.5598
Epoch 2/2... Discriminator Loss: 1.2074... Generator Loss: 1.0832
Epoch 2/2... Discriminator Loss: 1.8153... Generator Loss: 0.3356
Epoch 2/2... Discriminator Loss: 1.2754... Generator Loss: 0.7353
Epoch 2/2... Discriminator Loss: 1.1942... Generator Loss: 1.0425
Epoch 2/2... Discriminator Loss: 1.2373... Generator Loss: 1.0852
Epoch 2/2... Discriminator Loss: 1.2584... Generator Loss: 0.8505
Epoch 2/2... Discriminator Loss: 1.1584... Generator Loss: 0.7900
Epoch 2/2... Discriminator Loss: 1.2925... Generator Loss: 0.7404
Epoch 2/2... Discriminator Loss: 1.1197... Generator Loss: 0.9292
Epoch 2/2... Discriminator Loss: 1.2485... Generator Loss: 0.7787
Epoch 2/2... Discriminator Loss: 1.2057... Generator Loss: 0.7300
Epoch 2/2... Discriminator Loss: 1.5574... Generator Loss: 0.4205
Epoch 2/2... Discriminator Loss: 1.0571... Generator Loss: 1.1118
Epoch 2/2... Discriminator Loss: 1.0487... Generator Loss: 0.7677
Epoch 2/2... Discriminator Loss: 1.3570... Generator Loss: 0.7660
Epoch 2/2... Discriminator Loss: 1.9057... Generator Loss: 0.3858
Epoch 2/2... Discriminator Loss: 1.1871... Generator Loss: 0.7820
Epoch 2/2... Discriminator Loss: 1.3831... Generator Loss: 0.7238
Epoch 2/2... Discriminator Loss: 1.2068... Generator Loss: 0.7391
Epoch 2/2... Discriminator Loss: 1.1241... Generator Loss: 0.7916
Epoch 2/2... Discriminator Loss: 1.1907... Generator Loss: 0.7565
Epoch 2/2... Discriminator Loss: 1.2013... Generator Loss: 0.7637
Epoch 2/2... Discriminator Loss: 1.1512... Generator Loss: 1.0359
Epoch 2/2... Discriminator Loss: 1.1015... Generator Loss: 0.8386
Epoch 2/2... Discriminator Loss: 1.2952... Generator Loss: 0.6877
Epoch 2/2... Discriminator Loss: 1.0365... Generator Loss: 0.9493
Epoch 2/2... Discriminator Loss: 1.3289... Generator Loss: 0.6333
Epoch 2/2... Discriminator Loss: 1.2339... Generator Loss: 0.7575
Epoch 2/2... Discriminator Loss: 1.6141... Generator Loss: 0.4532
Epoch 2/2... Discriminator Loss: 1.0460... Generator Loss: 1.2395
Epoch 2/2... Discriminator Loss: 1.3659... Generator Loss: 0.9157
Epoch 2/2... Discriminator Loss: 1.2309... Generator Loss: 0.7648
Epoch 2/2... Discriminator Loss: 0.9155... Generator Loss: 1.0731
Epoch 2/2... Discriminator Loss: 1.8370... Generator Loss: 0.7915
Epoch 2/2... Discriminator Loss: 1.1302... Generator Loss: 0.8039
Epoch 2/2... Discriminator Loss: 1.5171... Generator Loss: 1.5656
Epoch 2/2... Discriminator Loss: 1.0575... Generator Loss: 1.0510
Epoch 2/2... Discriminator Loss: 1.4094... Generator Loss: 0.5640
Epoch 2/2... Discriminator Loss: 1.2267... Generator Loss: 0.7326
Epoch 2/2... Discriminator Loss: 1.1464... Generator Loss: 0.8835
Epoch 2/2... Discriminator Loss: 1.3793... Generator Loss: 0.6780
Epoch 2/2... Discriminator Loss: 1.2293... Generator Loss: 0.9448
Epoch 2/2... Discriminator Loss: 1.1503... Generator Loss: 0.6859
Epoch 2/2... Discriminator Loss: 1.2136... Generator Loss: 0.8558
Epoch 2/2... Discriminator Loss: 1.0552... Generator Loss: 0.7666

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [14]:
beta1 = 0.5
z_dim = 100


batch_size = 32
learning_rate = 0.002

g_keep_prob = 0.5
d_keep_prob = 0.9

"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode, g_keep_prob, d_keep_prob)
Epoch 1/1... Discriminator Loss: 4.0831... Generator Loss: 0.0670
Epoch 1/1... Discriminator Loss: 2.3387... Generator Loss: 0.5286
Epoch 1/1... Discriminator Loss: 2.8425... Generator Loss: 4.2876
Epoch 1/1... Discriminator Loss: 1.8664... Generator Loss: 1.7800
Epoch 1/1... Discriminator Loss: 3.2032... Generator Loss: 0.1659
Epoch 1/1... Discriminator Loss: 0.9555... Generator Loss: 1.2715
Epoch 1/1... Discriminator Loss: 1.1847... Generator Loss: 2.5546
Epoch 1/1... Discriminator Loss: 1.5517... Generator Loss: 0.5056
Epoch 1/1... Discriminator Loss: 2.6492... Generator Loss: 0.9352
Epoch 1/1... Discriminator Loss: 1.6899... Generator Loss: 0.6317
Epoch 1/1... Discriminator Loss: 1.0605... Generator Loss: 1.1802
Epoch 1/1... Discriminator Loss: 1.7280... Generator Loss: 0.4160
Epoch 1/1... Discriminator Loss: 2.1602... Generator Loss: 1.2506
Epoch 1/1... Discriminator Loss: 1.8071... Generator Loss: 0.6495
Epoch 1/1... Discriminator Loss: 1.3312... Generator Loss: 0.8516
Epoch 1/1... Discriminator Loss: 1.5460... Generator Loss: 0.8226
Epoch 1/1... Discriminator Loss: 1.3945... Generator Loss: 0.8494
Epoch 1/1... Discriminator Loss: 1.6424... Generator Loss: 0.6541
Epoch 1/1... Discriminator Loss: 1.4317... Generator Loss: 0.7603
Epoch 1/1... Discriminator Loss: 1.9748... Generator Loss: 0.3524
Epoch 1/1... Discriminator Loss: 1.7174... Generator Loss: 0.5792
Epoch 1/1... Discriminator Loss: 1.5497... Generator Loss: 0.9460
Epoch 1/1... Discriminator Loss: 1.4615... Generator Loss: 0.7460
Epoch 1/1... Discriminator Loss: 2.0780... Generator Loss: 0.4437
Epoch 1/1... Discriminator Loss: 1.5467... Generator Loss: 0.7755
Epoch 1/1... Discriminator Loss: 2.1397... Generator Loss: 0.9526
Epoch 1/1... Discriminator Loss: 1.5011... Generator Loss: 0.6080
Epoch 1/1... Discriminator Loss: 1.4040... Generator Loss: 0.7836
Epoch 1/1... Discriminator Loss: 1.5702... Generator Loss: 0.7533
Epoch 1/1... Discriminator Loss: 1.5367... Generator Loss: 0.6275
Epoch 1/1... Discriminator Loss: 1.4512... Generator Loss: 0.8624
Epoch 1/1... Discriminator Loss: 1.5645... Generator Loss: 0.7326
Epoch 1/1... Discriminator Loss: 1.6555... Generator Loss: 0.6150
Epoch 1/1... Discriminator Loss: 1.7349... Generator Loss: 0.4694
Epoch 1/1... Discriminator Loss: 1.6741... Generator Loss: 0.5411
Epoch 1/1... Discriminator Loss: 1.5963... Generator Loss: 0.5852
Epoch 1/1... Discriminator Loss: 1.4078... Generator Loss: 0.8778
Epoch 1/1... Discriminator Loss: 1.5037... Generator Loss: 0.5392
Epoch 1/1... Discriminator Loss: 1.2867... Generator Loss: 0.7923
Epoch 1/1... Discriminator Loss: 1.8134... Generator Loss: 0.4572
Epoch 1/1... Discriminator Loss: 1.4495... Generator Loss: 0.5899
Epoch 1/1... Discriminator Loss: 1.6552... Generator Loss: 0.5259
Epoch 1/1... Discriminator Loss: 1.4325... Generator Loss: 0.6982
Epoch 1/1... Discriminator Loss: 1.4660... Generator Loss: 0.6485
Epoch 1/1... Discriminator Loss: 1.8131... Generator Loss: 0.5448
Epoch 1/1... Discriminator Loss: 1.6347... Generator Loss: 0.4776
Epoch 1/1... Discriminator Loss: 1.5723... Generator Loss: 0.5448
Epoch 1/1... Discriminator Loss: 1.5514... Generator Loss: 0.7629
Epoch 1/1... Discriminator Loss: 1.6914... Generator Loss: 1.0519
Epoch 1/1... Discriminator Loss: 1.5324... Generator Loss: 0.7169
Epoch 1/1... Discriminator Loss: 1.4528... Generator Loss: 0.6226
Epoch 1/1... Discriminator Loss: 1.5651... Generator Loss: 0.6289
Epoch 1/1... Discriminator Loss: 1.4602... Generator Loss: 0.7856
Epoch 1/1... Discriminator Loss: 1.4489... Generator Loss: 0.7032
Epoch 1/1... Discriminator Loss: 1.6996... Generator Loss: 0.7426
Epoch 1/1... Discriminator Loss: 1.6357... Generator Loss: 0.5630
Epoch 1/1... Discriminator Loss: 1.6386... Generator Loss: 0.5959
Epoch 1/1... Discriminator Loss: 1.4500... Generator Loss: 0.7656
Epoch 1/1... Discriminator Loss: 1.5822... Generator Loss: 0.5731
Epoch 1/1... Discriminator Loss: 1.4387... Generator Loss: 0.7380
Epoch 1/1... Discriminator Loss: 1.8315... Generator Loss: 0.4677
Epoch 1/1... Discriminator Loss: 1.5097... Generator Loss: 0.7017
Epoch 1/1... Discriminator Loss: 1.4616... Generator Loss: 0.6783
Epoch 1/1... Discriminator Loss: 1.6257... Generator Loss: 0.6183
Epoch 1/1... Discriminator Loss: 1.5503... Generator Loss: 0.6902
Epoch 1/1... Discriminator Loss: 1.4408... Generator Loss: 0.6848
Epoch 1/1... Discriminator Loss: 1.4892... Generator Loss: 0.6391
Epoch 1/1... Discriminator Loss: 1.4007... Generator Loss: 0.9239
Epoch 1/1... Discriminator Loss: 1.4163... Generator Loss: 0.9328
Epoch 1/1... Discriminator Loss: 1.6764... Generator Loss: 0.6145
Epoch 1/1... Discriminator Loss: 1.4657... Generator Loss: 0.7660
Epoch 1/1... Discriminator Loss: 1.5581... Generator Loss: 0.6590
Epoch 1/1... Discriminator Loss: 1.5926... Generator Loss: 0.6941
Epoch 1/1... Discriminator Loss: 1.4920... Generator Loss: 0.5806
Epoch 1/1... Discriminator Loss: 1.6428... Generator Loss: 0.6863
Epoch 1/1... Discriminator Loss: 1.6514... Generator Loss: 0.6243
Epoch 1/1... Discriminator Loss: 1.4319... Generator Loss: 0.8539
Epoch 1/1... Discriminator Loss: 1.4363... Generator Loss: 0.7431
Epoch 1/1... Discriminator Loss: 1.8151... Generator Loss: 0.4449
Epoch 1/1... Discriminator Loss: 1.4612... Generator Loss: 0.7530
Epoch 1/1... Discriminator Loss: 1.5407... Generator Loss: 0.6775
Epoch 1/1... Discriminator Loss: 1.4509... Generator Loss: 0.8807
Epoch 1/1... Discriminator Loss: 1.3883... Generator Loss: 0.7960
Epoch 1/1... Discriminator Loss: 1.4512... Generator Loss: 0.7172
Epoch 1/1... Discriminator Loss: 1.4729... Generator Loss: 0.6045
Epoch 1/1... Discriminator Loss: 1.5527... Generator Loss: 0.6930
Epoch 1/1... Discriminator Loss: 1.4813... Generator Loss: 0.7313
Epoch 1/1... Discriminator Loss: 1.7995... Generator Loss: 0.4346
Epoch 1/1... Discriminator Loss: 1.4318... Generator Loss: 0.7627
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.6696
Epoch 1/1... Discriminator Loss: 1.4457... Generator Loss: 0.6502
Epoch 1/1... Discriminator Loss: 1.4568... Generator Loss: 0.8604
Epoch 1/1... Discriminator Loss: 1.5892... Generator Loss: 0.6545
Epoch 1/1... Discriminator Loss: 1.5529... Generator Loss: 0.6543
Epoch 1/1... Discriminator Loss: 1.5525... Generator Loss: 0.5223
Epoch 1/1... Discriminator Loss: 1.4000... Generator Loss: 0.8843
Epoch 1/1... Discriminator Loss: 1.3870... Generator Loss: 0.8203
Epoch 1/1... Discriminator Loss: 1.4746... Generator Loss: 0.6528
Epoch 1/1... Discriminator Loss: 1.4844... Generator Loss: 0.6396
Epoch 1/1... Discriminator Loss: 1.4280... Generator Loss: 0.6738
Epoch 1/1... Discriminator Loss: 1.4534... Generator Loss: 0.7397
Epoch 1/1... Discriminator Loss: 1.4390... Generator Loss: 0.7802
Epoch 1/1... Discriminator Loss: 1.4554... Generator Loss: 0.6994
Epoch 1/1... Discriminator Loss: 1.4474... Generator Loss: 0.7469
Epoch 1/1... Discriminator Loss: 1.4562... Generator Loss: 0.7542
Epoch 1/1... Discriminator Loss: 1.4847... Generator Loss: 0.7027
Epoch 1/1... Discriminator Loss: 1.4108... Generator Loss: 0.7725
Epoch 1/1... Discriminator Loss: 1.3667... Generator Loss: 0.8474
Epoch 1/1... Discriminator Loss: 1.7591... Generator Loss: 0.6291
Epoch 1/1... Discriminator Loss: 1.4731... Generator Loss: 0.6509
Epoch 1/1... Discriminator Loss: 1.4269... Generator Loss: 0.5620
Epoch 1/1... Discriminator Loss: 1.4483... Generator Loss: 0.7320
Epoch 1/1... Discriminator Loss: 1.6561... Generator Loss: 0.5946
Epoch 1/1... Discriminator Loss: 1.3750... Generator Loss: 0.7393
Epoch 1/1... Discriminator Loss: 1.6961... Generator Loss: 0.4814
Epoch 1/1... Discriminator Loss: 1.4264... Generator Loss: 0.7941
Epoch 1/1... Discriminator Loss: 1.4405... Generator Loss: 0.7464
Epoch 1/1... Discriminator Loss: 1.4494... Generator Loss: 0.8831
Epoch 1/1... Discriminator Loss: 1.6316... Generator Loss: 0.5126
Epoch 1/1... Discriminator Loss: 1.5085... Generator Loss: 0.6031
Epoch 1/1... Discriminator Loss: 1.3931... Generator Loss: 0.8286
Epoch 1/1... Discriminator Loss: 1.4139... Generator Loss: 0.7559
Epoch 1/1... Discriminator Loss: 1.4457... Generator Loss: 0.7825
Epoch 1/1... Discriminator Loss: 1.4864... Generator Loss: 0.8285
Epoch 1/1... Discriminator Loss: 1.4445... Generator Loss: 0.8456
Epoch 1/1... Discriminator Loss: 1.5258... Generator Loss: 0.8177
Epoch 1/1... Discriminator Loss: 1.5410... Generator Loss: 0.5896
Epoch 1/1... Discriminator Loss: 1.4478... Generator Loss: 0.6634
Epoch 1/1... Discriminator Loss: 1.3930... Generator Loss: 0.8301
Epoch 1/1... Discriminator Loss: 1.4488... Generator Loss: 0.7715
Epoch 1/1... Discriminator Loss: 1.4153... Generator Loss: 0.7443
Epoch 1/1... Discriminator Loss: 1.3654... Generator Loss: 0.7902
Epoch 1/1... Discriminator Loss: 1.4386... Generator Loss: 0.6663
Epoch 1/1... Discriminator Loss: 1.5639... Generator Loss: 0.5215
Epoch 1/1... Discriminator Loss: 1.4395... Generator Loss: 0.7177
Epoch 1/1... Discriminator Loss: 1.4041... Generator Loss: 0.6957
Epoch 1/1... Discriminator Loss: 1.3814... Generator Loss: 0.7939
Epoch 1/1... Discriminator Loss: 1.5637... Generator Loss: 0.5672
Epoch 1/1... Discriminator Loss: 1.4782... Generator Loss: 0.7936
Epoch 1/1... Discriminator Loss: 1.4513... Generator Loss: 0.7407
Epoch 1/1... Discriminator Loss: 1.4222... Generator Loss: 0.7502
Epoch 1/1... Discriminator Loss: 1.4102... Generator Loss: 0.7372
Epoch 1/1... Discriminator Loss: 1.4315... Generator Loss: 0.7181
Epoch 1/1... Discriminator Loss: 1.4725... Generator Loss: 0.6532
Epoch 1/1... Discriminator Loss: 1.4891... Generator Loss: 0.8364
Epoch 1/1... Discriminator Loss: 1.4968... Generator Loss: 0.8845
Epoch 1/1... Discriminator Loss: 1.4882... Generator Loss: 0.8445
Epoch 1/1... Discriminator Loss: 1.3525... Generator Loss: 0.7618
Epoch 1/1... Discriminator Loss: 1.4048... Generator Loss: 0.7806
Epoch 1/1... Discriminator Loss: 1.4902... Generator Loss: 0.7669
Epoch 1/1... Discriminator Loss: 1.4954... Generator Loss: 0.7993
Epoch 1/1... Discriminator Loss: 1.4847... Generator Loss: 0.6101
Epoch 1/1... Discriminator Loss: 1.4676... Generator Loss: 0.8255
Epoch 1/1... Discriminator Loss: 1.4716... Generator Loss: 0.7292
Epoch 1/1... Discriminator Loss: 1.3821... Generator Loss: 0.7868
Epoch 1/1... Discriminator Loss: 1.4575... Generator Loss: 0.7521
Epoch 1/1... Discriminator Loss: 1.4075... Generator Loss: 0.8022
Epoch 1/1... Discriminator Loss: 1.3527... Generator Loss: 0.6904
Epoch 1/1... Discriminator Loss: 1.8254... Generator Loss: 0.4583
Epoch 1/1... Discriminator Loss: 1.0507... Generator Loss: 1.5624
Epoch 1/1... Discriminator Loss: 0.9474... Generator Loss: 1.2566
Epoch 1/1... Discriminator Loss: 1.4240... Generator Loss: 0.5470
Epoch 1/1... Discriminator Loss: 1.6048... Generator Loss: 0.6341
Epoch 1/1... Discriminator Loss: 1.3914... Generator Loss: 0.7713
Epoch 1/1... Discriminator Loss: 1.6622... Generator Loss: 0.7856
Epoch 1/1... Discriminator Loss: 1.5465... Generator Loss: 0.6055
Epoch 1/1... Discriminator Loss: 1.3634... Generator Loss: 0.7706
Epoch 1/1... Discriminator Loss: 1.4798... Generator Loss: 0.6837
Epoch 1/1... Discriminator Loss: 1.5345... Generator Loss: 0.6669
Epoch 1/1... Discriminator Loss: 1.3789... Generator Loss: 0.8315
Epoch 1/1... Discriminator Loss: 1.4478... Generator Loss: 0.6475
Epoch 1/1... Discriminator Loss: 1.4032... Generator Loss: 0.7970
Epoch 1/1... Discriminator Loss: 1.4771... Generator Loss: 0.7216
Epoch 1/1... Discriminator Loss: 1.7042... Generator Loss: 0.5325
Epoch 1/1... Discriminator Loss: 1.4623... Generator Loss: 0.6596
Epoch 1/1... Discriminator Loss: 1.2473... Generator Loss: 0.7700
Epoch 1/1... Discriminator Loss: 1.4471... Generator Loss: 0.5610
Epoch 1/1... Discriminator Loss: 1.4508... Generator Loss: 0.7257
Epoch 1/1... Discriminator Loss: 1.3866... Generator Loss: 0.7798
Epoch 1/1... Discriminator Loss: 1.4223... Generator Loss: 0.7518
Epoch 1/1... Discriminator Loss: 1.4218... Generator Loss: 0.6986
Epoch 1/1... Discriminator Loss: 1.5356... Generator Loss: 0.6163
Epoch 1/1... Discriminator Loss: 1.4207... Generator Loss: 0.7535
Epoch 1/1... Discriminator Loss: 1.4588... Generator Loss: 0.7265
Epoch 1/1... Discriminator Loss: 1.4557... Generator Loss: 0.7786
Epoch 1/1... Discriminator Loss: 1.3814... Generator Loss: 0.7210
Epoch 1/1... Discriminator Loss: 1.4590... Generator Loss: 0.6962
Epoch 1/1... Discriminator Loss: 1.3876... Generator Loss: 0.7523
Epoch 1/1... Discriminator Loss: 1.3420... Generator Loss: 0.8035
Epoch 1/1... Discriminator Loss: 1.4122... Generator Loss: 0.8068
Epoch 1/1... Discriminator Loss: 1.4263... Generator Loss: 0.9849
Epoch 1/1... Discriminator Loss: 1.3542... Generator Loss: 0.7836
Epoch 1/1... Discriminator Loss: 1.4082... Generator Loss: 0.7501
Epoch 1/1... Discriminator Loss: 1.3705... Generator Loss: 0.8141
Epoch 1/1... Discriminator Loss: 1.4796... Generator Loss: 0.7231
Epoch 1/1... Discriminator Loss: 1.4025... Generator Loss: 0.7525
Epoch 1/1... Discriminator Loss: 1.4418... Generator Loss: 0.7269
Epoch 1/1... Discriminator Loss: 1.4706... Generator Loss: 0.8346
Epoch 1/1... Discriminator Loss: 1.4382... Generator Loss: 0.7177
Epoch 1/1... Discriminator Loss: 1.4434... Generator Loss: 0.8108
Epoch 1/1... Discriminator Loss: 1.4154... Generator Loss: 0.7552
Epoch 1/1... Discriminator Loss: 1.4308... Generator Loss: 0.6862
Epoch 1/1... Discriminator Loss: 1.4015... Generator Loss: 0.6922
Epoch 1/1... Discriminator Loss: 1.4851... Generator Loss: 0.7271
Epoch 1/1... Discriminator Loss: 1.4147... Generator Loss: 0.7618
Epoch 1/1... Discriminator Loss: 1.4507... Generator Loss: 0.6583
Epoch 1/1... Discriminator Loss: 1.4792... Generator Loss: 0.7205
Epoch 1/1... Discriminator Loss: 1.4858... Generator Loss: 0.7035
Epoch 1/1... Discriminator Loss: 1.3924... Generator Loss: 0.7774
Epoch 1/1... Discriminator Loss: 1.3905... Generator Loss: 0.7884
Epoch 1/1... Discriminator Loss: 1.5049... Generator Loss: 0.6879
Epoch 1/1... Discriminator Loss: 1.4190... Generator Loss: 0.6923
Epoch 1/1... Discriminator Loss: 1.3895... Generator Loss: 0.7269
Epoch 1/1... Discriminator Loss: 1.3711... Generator Loss: 0.8655
Epoch 1/1... Discriminator Loss: 1.4940... Generator Loss: 0.6591
Epoch 1/1... Discriminator Loss: 1.5691... Generator Loss: 0.6641
Epoch 1/1... Discriminator Loss: 1.4045... Generator Loss: 0.8183
Epoch 1/1... Discriminator Loss: 1.4728... Generator Loss: 0.5960
Epoch 1/1... Discriminator Loss: 1.4119... Generator Loss: 0.8234
Epoch 1/1... Discriminator Loss: 1.3803... Generator Loss: 0.7984
Epoch 1/1... Discriminator Loss: 1.4884... Generator Loss: 0.7118
Epoch 1/1... Discriminator Loss: 1.3557... Generator Loss: 0.8041
Epoch 1/1... Discriminator Loss: 1.3684... Generator Loss: 0.7508
Epoch 1/1... Discriminator Loss: 1.3890... Generator Loss: 0.7642
Epoch 1/1... Discriminator Loss: 1.4229... Generator Loss: 0.7876
Epoch 1/1... Discriminator Loss: 1.4428... Generator Loss: 0.7643
Epoch 1/1... Discriminator Loss: 1.3559... Generator Loss: 0.8410
Epoch 1/1... Discriminator Loss: 1.4124... Generator Loss: 0.8171
Epoch 1/1... Discriminator Loss: 1.3672... Generator Loss: 0.7907
Epoch 1/1... Discriminator Loss: 1.4497... Generator Loss: 0.7081
Epoch 1/1... Discriminator Loss: 1.4461... Generator Loss: 0.7112
Epoch 1/1... Discriminator Loss: 1.4076... Generator Loss: 0.7876
Epoch 1/1... Discriminator Loss: 1.3989... Generator Loss: 0.8174
Epoch 1/1... Discriminator Loss: 1.4104... Generator Loss: 0.7309
Epoch 1/1... Discriminator Loss: 1.4266... Generator Loss: 0.8057
Epoch 1/1... Discriminator Loss: 1.3824... Generator Loss: 0.7225
Epoch 1/1... Discriminator Loss: 1.4004... Generator Loss: 0.7839
Epoch 1/1... Discriminator Loss: 1.4426... Generator Loss: 0.7121
Epoch 1/1... Discriminator Loss: 1.3815... Generator Loss: 0.7916
Epoch 1/1... Discriminator Loss: 1.4111... Generator Loss: 0.7088
Epoch 1/1... Discriminator Loss: 1.3960... Generator Loss: 0.7474
Epoch 1/1... Discriminator Loss: 1.4117... Generator Loss: 0.7937
Epoch 1/1... Discriminator Loss: 1.3962... Generator Loss: 0.7750
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.8064
Epoch 1/1... Discriminator Loss: 1.4677... Generator Loss: 0.6921
Epoch 1/1... Discriminator Loss: 1.3941... Generator Loss: 0.7417
Epoch 1/1... Discriminator Loss: 1.3974... Generator Loss: 0.7245
Epoch 1/1... Discriminator Loss: 1.4044... Generator Loss: 0.7645
Epoch 1/1... Discriminator Loss: 1.4248... Generator Loss: 0.7568
Epoch 1/1... Discriminator Loss: 1.4216... Generator Loss: 0.7617
Epoch 1/1... Discriminator Loss: 1.4297... Generator Loss: 0.8004
Epoch 1/1... Discriminator Loss: 1.3974... Generator Loss: 0.7628
Epoch 1/1... Discriminator Loss: 1.4486... Generator Loss: 0.7423
Epoch 1/1... Discriminator Loss: 1.3903... Generator Loss: 0.7552
Epoch 1/1... Discriminator Loss: 1.4082... Generator Loss: 0.7970
Epoch 1/1... Discriminator Loss: 1.3610... Generator Loss: 0.7803
Epoch 1/1... Discriminator Loss: 1.4636... Generator Loss: 0.7244
Epoch 1/1... Discriminator Loss: 1.4118... Generator Loss: 0.7674
Epoch 1/1... Discriminator Loss: 1.3971... Generator Loss: 0.8140
Epoch 1/1... Discriminator Loss: 1.4257... Generator Loss: 0.6940
Epoch 1/1... Discriminator Loss: 1.4366... Generator Loss: 0.7290
Epoch 1/1... Discriminator Loss: 1.3604... Generator Loss: 0.8086
Epoch 1/1... Discriminator Loss: 1.4035... Generator Loss: 0.8011
Epoch 1/1... Discriminator Loss: 1.4485... Generator Loss: 0.7192
Epoch 1/1... Discriminator Loss: 1.4374... Generator Loss: 0.6598
Epoch 1/1... Discriminator Loss: 1.3873... Generator Loss: 0.7886
Epoch 1/1... Discriminator Loss: 1.4059... Generator Loss: 0.7926
Epoch 1/1... Discriminator Loss: 1.4238... Generator Loss: 0.7337
Epoch 1/1... Discriminator Loss: 1.3965... Generator Loss: 0.7834
Epoch 1/1... Discriminator Loss: 1.4146... Generator Loss: 0.8005
Epoch 1/1... Discriminator Loss: 1.4057... Generator Loss: 0.7024
Epoch 1/1... Discriminator Loss: 1.4165... Generator Loss: 0.7779
Epoch 1/1... Discriminator Loss: 1.3858... Generator Loss: 0.7469
Epoch 1/1... Discriminator Loss: 1.4318... Generator Loss: 0.7595
Epoch 1/1... Discriminator Loss: 1.3844... Generator Loss: 0.8190
Epoch 1/1... Discriminator Loss: 1.4489... Generator Loss: 0.8156
Epoch 1/1... Discriminator Loss: 1.3474... Generator Loss: 0.7998
Epoch 1/1... Discriminator Loss: 1.4293... Generator Loss: 0.7307
Epoch 1/1... Discriminator Loss: 1.4033... Generator Loss: 0.8011
Epoch 1/1... Discriminator Loss: 1.3908... Generator Loss: 0.7818
Epoch 1/1... Discriminator Loss: 1.3780... Generator Loss: 0.7684
Epoch 1/1... Discriminator Loss: 1.5728... Generator Loss: 0.6452
Epoch 1/1... Discriminator Loss: 1.4024... Generator Loss: 0.9129
Epoch 1/1... Discriminator Loss: 1.4817... Generator Loss: 0.7311
Epoch 1/1... Discriminator Loss: 1.3864... Generator Loss: 0.7482
Epoch 1/1... Discriminator Loss: 1.3948... Generator Loss: 0.7702
Epoch 1/1... Discriminator Loss: 1.3696... Generator Loss: 0.8315
Epoch 1/1... Discriminator Loss: 1.4073... Generator Loss: 0.7395
Epoch 1/1... Discriminator Loss: 1.4442... Generator Loss: 0.7954
Epoch 1/1... Discriminator Loss: 1.5032... Generator Loss: 0.7531
Epoch 1/1... Discriminator Loss: 1.4024... Generator Loss: 0.7831
Epoch 1/1... Discriminator Loss: 1.4287... Generator Loss: 0.7687
Epoch 1/1... Discriminator Loss: 1.4103... Generator Loss: 0.7737
Epoch 1/1... Discriminator Loss: 1.3713... Generator Loss: 0.7341
Epoch 1/1... Discriminator Loss: 1.3940... Generator Loss: 0.8259
Epoch 1/1... Discriminator Loss: 1.4527... Generator Loss: 0.7273
Epoch 1/1... Discriminator Loss: 1.4033... Generator Loss: 0.8105
Epoch 1/1... Discriminator Loss: 1.4409... Generator Loss: 0.7606
Epoch 1/1... Discriminator Loss: 1.3579... Generator Loss: 0.7528
Epoch 1/1... Discriminator Loss: 1.3658... Generator Loss: 0.8094
Epoch 1/1... Discriminator Loss: 1.3924... Generator Loss: 0.7788
Epoch 1/1... Discriminator Loss: 1.4217... Generator Loss: 0.6887
Epoch 1/1... Discriminator Loss: 1.3817... Generator Loss: 0.7894
Epoch 1/1... Discriminator Loss: 1.3702... Generator Loss: 0.7626
Epoch 1/1... Discriminator Loss: 1.5204... Generator Loss: 0.7081
Epoch 1/1... Discriminator Loss: 1.4167... Generator Loss: 0.7370
Epoch 1/1... Discriminator Loss: 1.4225... Generator Loss: 0.8225
Epoch 1/1... Discriminator Loss: 1.4276... Generator Loss: 0.7465
Epoch 1/1... Discriminator Loss: 1.4038... Generator Loss: 0.8183
Epoch 1/1... Discriminator Loss: 1.4330... Generator Loss: 0.8010
Epoch 1/1... Discriminator Loss: 1.3936... Generator Loss: 0.7388
Epoch 1/1... Discriminator Loss: 1.4614... Generator Loss: 0.7199
Epoch 1/1... Discriminator Loss: 1.4263... Generator Loss: 0.7264
Epoch 1/1... Discriminator Loss: 1.4042... Generator Loss: 0.7770
Epoch 1/1... Discriminator Loss: 1.4080... Generator Loss: 0.7609
Epoch 1/1... Discriminator Loss: 1.3863... Generator Loss: 0.7860
Epoch 1/1... Discriminator Loss: 1.4016... Generator Loss: 0.8240
Epoch 1/1... Discriminator Loss: 1.3835... Generator Loss: 0.7938
Epoch 1/1... Discriminator Loss: 1.3777... Generator Loss: 0.7953
Epoch 1/1... Discriminator Loss: 1.4129... Generator Loss: 0.7889
Epoch 1/1... Discriminator Loss: 1.4139... Generator Loss: 0.7930
Epoch 1/1... Discriminator Loss: 1.4003... Generator Loss: 0.8260
Epoch 1/1... Discriminator Loss: 1.4019... Generator Loss: 0.7337
Epoch 1/1... Discriminator Loss: 1.3818... Generator Loss: 0.8231
Epoch 1/1... Discriminator Loss: 1.3875... Generator Loss: 0.8008
Epoch 1/1... Discriminator Loss: 1.4494... Generator Loss: 0.7056
Epoch 1/1... Discriminator Loss: 1.4171... Generator Loss: 0.7439
Epoch 1/1... Discriminator Loss: 1.4248... Generator Loss: 0.7658
Epoch 1/1... Discriminator Loss: 1.3995... Generator Loss: 0.7936
Epoch 1/1... Discriminator Loss: 1.4153... Generator Loss: 0.7104
Epoch 1/1... Discriminator Loss: 1.4254... Generator Loss: 0.8012
Epoch 1/1... Discriminator Loss: 1.3834... Generator Loss: 0.7895
Epoch 1/1... Discriminator Loss: 1.4440... Generator Loss: 0.7709
Epoch 1/1... Discriminator Loss: 1.4030... Generator Loss: 0.7883
Epoch 1/1... Discriminator Loss: 1.4022... Generator Loss: 0.8060
Epoch 1/1... Discriminator Loss: 1.4081... Generator Loss: 0.7666
Epoch 1/1... Discriminator Loss: 1.4311... Generator Loss: 0.7508
Epoch 1/1... Discriminator Loss: 1.3987... Generator Loss: 0.8273
Epoch 1/1... Discriminator Loss: 1.4164... Generator Loss: 0.7439
Epoch 1/1... Discriminator Loss: 1.4302... Generator Loss: 0.7759
Epoch 1/1... Discriminator Loss: 1.3914... Generator Loss: 0.7887
Epoch 1/1... Discriminator Loss: 1.3950... Generator Loss: 0.7771
Epoch 1/1... Discriminator Loss: 1.4106... Generator Loss: 0.8106
Epoch 1/1... Discriminator Loss: 1.4215... Generator Loss: 0.7622
Epoch 1/1... Discriminator Loss: 1.3949... Generator Loss: 0.7985
Epoch 1/1... Discriminator Loss: 1.3981... Generator Loss: 0.7247
Epoch 1/1... Discriminator Loss: 1.3829... Generator Loss: 0.7842
Epoch 1/1... Discriminator Loss: 1.3989... Generator Loss: 0.8219
Epoch 1/1... Discriminator Loss: 1.4052... Generator Loss: 0.7779
Epoch 1/1... Discriminator Loss: 1.4004... Generator Loss: 0.7430
Epoch 1/1... Discriminator Loss: 1.4031... Generator Loss: 0.7636
Epoch 1/1... Discriminator Loss: 1.3950... Generator Loss: 0.7758
Epoch 1/1... Discriminator Loss: 1.4270... Generator Loss: 0.7809
Epoch 1/1... Discriminator Loss: 1.4050... Generator Loss: 0.7313
Epoch 1/1... Discriminator Loss: 1.3869... Generator Loss: 0.7834
Epoch 1/1... Discriminator Loss: 1.4282... Generator Loss: 0.7869
Epoch 1/1... Discriminator Loss: 1.4099... Generator Loss: 0.8334
Epoch 1/1... Discriminator Loss: 1.3889... Generator Loss: 0.8155
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.7411
Epoch 1/1... Discriminator Loss: 1.4163... Generator Loss: 0.7468
Epoch 1/1... Discriminator Loss: 1.5191... Generator Loss: 0.6799
Epoch 1/1... Discriminator Loss: 1.4327... Generator Loss: 0.7631
Epoch 1/1... Discriminator Loss: 1.4036... Generator Loss: 0.7888
Epoch 1/1... Discriminator Loss: 1.4263... Generator Loss: 0.7620
Epoch 1/1... Discriminator Loss: 1.4031... Generator Loss: 0.7458
Epoch 1/1... Discriminator Loss: 1.4011... Generator Loss: 0.7639
Epoch 1/1... Discriminator Loss: 1.4305... Generator Loss: 0.7354
Epoch 1/1... Discriminator Loss: 1.4527... Generator Loss: 0.7318
Epoch 1/1... Discriminator Loss: 1.5207... Generator Loss: 0.6796
Epoch 1/1... Discriminator Loss: 1.3932... Generator Loss: 0.7972
Epoch 1/1... Discriminator Loss: 1.4025... Generator Loss: 0.7785
Epoch 1/1... Discriminator Loss: 1.4026... Generator Loss: 0.7958
Epoch 1/1... Discriminator Loss: 1.4198... Generator Loss: 0.7567
Epoch 1/1... Discriminator Loss: 1.4100... Generator Loss: 0.7455
Epoch 1/1... Discriminator Loss: 1.3899... Generator Loss: 0.8093
Epoch 1/1... Discriminator Loss: 1.3934... Generator Loss: 0.7610
Epoch 1/1... Discriminator Loss: 1.4043... Generator Loss: 0.7873
Epoch 1/1... Discriminator Loss: 1.3999... Generator Loss: 0.7892
Epoch 1/1... Discriminator Loss: 1.4133... Generator Loss: 0.7776
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.7865
Epoch 1/1... Discriminator Loss: 1.4011... Generator Loss: 0.7588
Epoch 1/1... Discriminator Loss: 1.4115... Generator Loss: 0.7957
Epoch 1/1... Discriminator Loss: 1.4020... Generator Loss: 0.7912
Epoch 1/1... Discriminator Loss: 1.3991... Generator Loss: 0.7926
Epoch 1/1... Discriminator Loss: 1.3899... Generator Loss: 0.7770
Epoch 1/1... Discriminator Loss: 1.3893... Generator Loss: 0.8170
Epoch 1/1... Discriminator Loss: 1.3804... Generator Loss: 0.7970
Epoch 1/1... Discriminator Loss: 1.3710... Generator Loss: 0.7807
Epoch 1/1... Discriminator Loss: 1.3948... Generator Loss: 0.7682
Epoch 1/1... Discriminator Loss: 1.4152... Generator Loss: 0.7381
Epoch 1/1... Discriminator Loss: 1.4097... Generator Loss: 0.7052
Epoch 1/1... Discriminator Loss: 1.4392... Generator Loss: 0.6948
Epoch 1/1... Discriminator Loss: 1.4248... Generator Loss: 0.7897
Epoch 1/1... Discriminator Loss: 1.3898... Generator Loss: 0.7966
Epoch 1/1... Discriminator Loss: 1.3937... Generator Loss: 0.7766
Epoch 1/1... Discriminator Loss: 1.4077... Generator Loss: 0.7460
Epoch 1/1... Discriminator Loss: 1.3677... Generator Loss: 0.8052
Epoch 1/1... Discriminator Loss: 1.3942... Generator Loss: 0.7996
Epoch 1/1... Discriminator Loss: 1.3770... Generator Loss: 0.7839
Epoch 1/1... Discriminator Loss: 1.3795... Generator Loss: 0.7611
Epoch 1/1... Discriminator Loss: 1.4261... Generator Loss: 0.7526
Epoch 1/1... Discriminator Loss: 1.4025... Generator Loss: 0.7795
Epoch 1/1... Discriminator Loss: 1.3877... Generator Loss: 0.7933
Epoch 1/1... Discriminator Loss: 1.3921... Generator Loss: 0.7869
Epoch 1/1... Discriminator Loss: 1.3788... Generator Loss: 0.7724
Epoch 1/1... Discriminator Loss: 1.4122... Generator Loss: 0.7561
Epoch 1/1... Discriminator Loss: 1.4111... Generator Loss: 0.7927
Epoch 1/1... Discriminator Loss: 1.4024... Generator Loss: 0.7910
Epoch 1/1... Discriminator Loss: 1.4170... Generator Loss: 0.7383
Epoch 1/1... Discriminator Loss: 1.4494... Generator Loss: 0.7468
Epoch 1/1... Discriminator Loss: 1.3871... Generator Loss: 0.7145
Epoch 1/1... Discriminator Loss: 1.4383... Generator Loss: 0.7606
Epoch 1/1... Discriminator Loss: 1.4075... Generator Loss: 0.8331
Epoch 1/1... Discriminator Loss: 1.4054... Generator Loss: 0.7662
Epoch 1/1... Discriminator Loss: 1.3960... Generator Loss: 0.7746
Epoch 1/1... Discriminator Loss: 1.3960... Generator Loss: 0.7510
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.7696
Epoch 1/1... Discriminator Loss: 1.4720... Generator Loss: 0.7808
Epoch 1/1... Discriminator Loss: 1.4032... Generator Loss: 0.7457
Epoch 1/1... Discriminator Loss: 1.3990... Generator Loss: 0.7478
Epoch 1/1... Discriminator Loss: 1.4164... Generator Loss: 0.7856
Epoch 1/1... Discriminator Loss: 1.4380... Generator Loss: 0.7729
Epoch 1/1... Discriminator Loss: 1.4470... Generator Loss: 0.7018
Epoch 1/1... Discriminator Loss: 1.3685... Generator Loss: 0.7977
Epoch 1/1... Discriminator Loss: 1.4092... Generator Loss: 0.7290
Epoch 1/1... Discriminator Loss: 1.4286... Generator Loss: 0.7589
Epoch 1/1... Discriminator Loss: 1.4074... Generator Loss: 0.7423
Epoch 1/1... Discriminator Loss: 1.4225... Generator Loss: 0.7741
Epoch 1/1... Discriminator Loss: 1.3950... Generator Loss: 0.7524
Epoch 1/1... Discriminator Loss: 1.4300... Generator Loss: 0.7592
Epoch 1/1... Discriminator Loss: 1.3874... Generator Loss: 0.7692
Epoch 1/1... Discriminator Loss: 1.4006... Generator Loss: 0.7726
Epoch 1/1... Discriminator Loss: 1.3734... Generator Loss: 0.7807
Epoch 1/1... Discriminator Loss: 1.4005... Generator Loss: 0.7513
Epoch 1/1... Discriminator Loss: 1.4280... Generator Loss: 0.7665
Epoch 1/1... Discriminator Loss: 1.3827... Generator Loss: 0.7783
Epoch 1/1... Discriminator Loss: 1.3976... Generator Loss: 0.7839
Epoch 1/1... Discriminator Loss: 1.4043... Generator Loss: 0.7790
Epoch 1/1... Discriminator Loss: 1.3794... Generator Loss: 0.7917
Epoch 1/1... Discriminator Loss: 1.3824... Generator Loss: 0.7762
Epoch 1/1... Discriminator Loss: 1.3935... Generator Loss: 0.7570
Epoch 1/1... Discriminator Loss: 1.3893... Generator Loss: 0.7896
Epoch 1/1... Discriminator Loss: 1.4027... Generator Loss: 0.7741
Epoch 1/1... Discriminator Loss: 1.3838... Generator Loss: 0.7848
Epoch 1/1... Discriminator Loss: 1.3969... Generator Loss: 0.7981
Epoch 1/1... Discriminator Loss: 1.4163... Generator Loss: 0.7872
Epoch 1/1... Discriminator Loss: 1.4138... Generator Loss: 0.7756
Epoch 1/1... Discriminator Loss: 1.4284... Generator Loss: 0.7647
Epoch 1/1... Discriminator Loss: 1.3899... Generator Loss: 0.8171
Epoch 1/1... Discriminator Loss: 1.4161... Generator Loss: 0.7195
Epoch 1/1... Discriminator Loss: 1.4034... Generator Loss: 0.7685
Epoch 1/1... Discriminator Loss: 1.3970... Generator Loss: 0.8057
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.8037
Epoch 1/1... Discriminator Loss: 1.3871... Generator Loss: 0.7866
Epoch 1/1... Discriminator Loss: 1.4007... Generator Loss: 0.7704
Epoch 1/1... Discriminator Loss: 1.3645... Generator Loss: 0.7920
Epoch 1/1... Discriminator Loss: 1.3933... Generator Loss: 0.7678
Epoch 1/1... Discriminator Loss: 1.3845... Generator Loss: 0.7920
Epoch 1/1... Discriminator Loss: 1.4137... Generator Loss: 0.7472
Epoch 1/1... Discriminator Loss: 1.4819... Generator Loss: 0.7208
Epoch 1/1... Discriminator Loss: 1.3961... Generator Loss: 0.7669
Epoch 1/1... Discriminator Loss: 1.4151... Generator Loss: 0.7173
Epoch 1/1... Discriminator Loss: 1.3806... Generator Loss: 0.7850
Epoch 1/1... Discriminator Loss: 1.4107... Generator Loss: 0.7919
Epoch 1/1... Discriminator Loss: 1.3928... Generator Loss: 0.7754
Epoch 1/1... Discriminator Loss: 1.3769... Generator Loss: 0.7786
Epoch 1/1... Discriminator Loss: 1.4312... Generator Loss: 0.7477
Epoch 1/1... Discriminator Loss: 1.4627... Generator Loss: 0.7495
Epoch 1/1... Discriminator Loss: 1.3941... Generator Loss: 0.7789
Epoch 1/1... Discriminator Loss: 1.4065... Generator Loss: 0.7763
Epoch 1/1... Discriminator Loss: 1.3970... Generator Loss: 0.7974
Epoch 1/1... Discriminator Loss: 1.4008... Generator Loss: 0.7909
Epoch 1/1... Discriminator Loss: 1.3935... Generator Loss: 0.7777
Epoch 1/1... Discriminator Loss: 1.3877... Generator Loss: 0.8003
Epoch 1/1... Discriminator Loss: 1.3935... Generator Loss: 0.7646
Epoch 1/1... Discriminator Loss: 1.3919... Generator Loss: 0.7848
Epoch 1/1... Discriminator Loss: 1.3855... Generator Loss: 0.7766
Epoch 1/1... Discriminator Loss: 1.3896... Generator Loss: 0.7722
Epoch 1/1... Discriminator Loss: 1.3942... Generator Loss: 0.7894
Epoch 1/1... Discriminator Loss: 1.3869... Generator Loss: 0.7682
Epoch 1/1... Discriminator Loss: 1.3775... Generator Loss: 0.7794
Epoch 1/1... Discriminator Loss: 1.3852... Generator Loss: 0.7990
Epoch 1/1... Discriminator Loss: 1.3910... Generator Loss: 0.8122
Epoch 1/1... Discriminator Loss: 1.3967... Generator Loss: 0.7702
Epoch 1/1... Discriminator Loss: 1.3933... Generator Loss: 0.7399
Epoch 1/1... Discriminator Loss: 1.4156... Generator Loss: 0.7556
Epoch 1/1... Discriminator Loss: 1.3809... Generator Loss: 0.7750
Epoch 1/1... Discriminator Loss: 1.3954... Generator Loss: 0.7678
Epoch 1/1... Discriminator Loss: 1.3632... Generator Loss: 0.8035
Epoch 1/1... Discriminator Loss: 1.3853... Generator Loss: 0.7683
Epoch 1/1... Discriminator Loss: 1.3836... Generator Loss: 0.7827
Epoch 1/1... Discriminator Loss: 1.3720... Generator Loss: 0.7836
Epoch 1/1... Discriminator Loss: 1.4066... Generator Loss: 0.7866
Epoch 1/1... Discriminator Loss: 1.3915... Generator Loss: 0.8001
Epoch 1/1... Discriminator Loss: 1.4174... Generator Loss: 0.7575
Epoch 1/1... Discriminator Loss: 1.4205... Generator Loss: 0.7496
Epoch 1/1... Discriminator Loss: 1.4050... Generator Loss: 0.7717
Epoch 1/1... Discriminator Loss: 1.3996... Generator Loss: 0.7655
Epoch 1/1... Discriminator Loss: 1.3952... Generator Loss: 0.7852
Epoch 1/1... Discriminator Loss: 1.3897... Generator Loss: 0.7861
Epoch 1/1... Discriminator Loss: 1.4085... Generator Loss: 0.7652
Epoch 1/1... Discriminator Loss: 1.4450... Generator Loss: 0.7551
Epoch 1/1... Discriminator Loss: 1.3996... Generator Loss: 0.7679
Epoch 1/1... Discriminator Loss: 1.4119... Generator Loss: 0.7876
Epoch 1/1... Discriminator Loss: 1.3732... Generator Loss: 0.8229
Epoch 1/1... Discriminator Loss: 1.4055... Generator Loss: 0.7852
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.7938
Epoch 1/1... Discriminator Loss: 1.3715... Generator Loss: 0.7809
Epoch 1/1... Discriminator Loss: 1.3912... Generator Loss: 0.7582
Epoch 1/1... Discriminator Loss: 1.4221... Generator Loss: 0.7574
Epoch 1/1... Discriminator Loss: 1.4548... Generator Loss: 0.7524
Epoch 1/1... Discriminator Loss: 1.3791... Generator Loss: 0.8396
Epoch 1/1... Discriminator Loss: 1.4207... Generator Loss: 0.7530
Epoch 1/1... Discriminator Loss: 1.3983... Generator Loss: 0.7954
Epoch 1/1... Discriminator Loss: 1.3738... Generator Loss: 0.7898
Epoch 1/1... Discriminator Loss: 1.4003... Generator Loss: 0.7750
Epoch 1/1... Discriminator Loss: 1.3869... Generator Loss: 0.7733
Epoch 1/1... Discriminator Loss: 1.3952... Generator Loss: 0.7857
Epoch 1/1... Discriminator Loss: 1.3998... Generator Loss: 0.7854
Epoch 1/1... Discriminator Loss: 1.4088... Generator Loss: 0.7690
Epoch 1/1... Discriminator Loss: 1.3785... Generator Loss: 0.8004
Epoch 1/1... Discriminator Loss: 1.4090... Generator Loss: 0.7428
Epoch 1/1... Discriminator Loss: 1.3864... Generator Loss: 0.7784
Epoch 1/1... Discriminator Loss: 1.4012... Generator Loss: 0.7736
Epoch 1/1... Discriminator Loss: 1.3907... Generator Loss: 0.7932
Epoch 1/1... Discriminator Loss: 1.3818... Generator Loss: 0.7846
Epoch 1/1... Discriminator Loss: 1.4018... Generator Loss: 0.7779
Epoch 1/1... Discriminator Loss: 1.4003... Generator Loss: 0.7702
Epoch 1/1... Discriminator Loss: 1.4065... Generator Loss: 0.7717
Epoch 1/1... Discriminator Loss: 1.4074... Generator Loss: 0.7426
Epoch 1/1... Discriminator Loss: 1.4153... Generator Loss: 0.7669
Epoch 1/1... Discriminator Loss: 1.4045... Generator Loss: 0.7978
Epoch 1/1... Discriminator Loss: 1.3784... Generator Loss: 0.7904
Epoch 1/1... Discriminator Loss: 1.3889... Generator Loss: 0.7722
Epoch 1/1... Discriminator Loss: 1.3984... Generator Loss: 0.7735
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.7760
Epoch 1/1... Discriminator Loss: 1.3746... Generator Loss: 0.7938
Epoch 1/1... Discriminator Loss: 1.4079... Generator Loss: 0.7571
Epoch 1/1... Discriminator Loss: 1.3847... Generator Loss: 0.7716
Epoch 1/1... Discriminator Loss: 1.3946... Generator Loss: 0.7771
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.7670
Epoch 1/1... Discriminator Loss: 1.3756... Generator Loss: 0.8163
Epoch 1/1... Discriminator Loss: 1.3907... Generator Loss: 0.7684
Epoch 1/1... Discriminator Loss: 1.3911... Generator Loss: 0.7701
Epoch 1/1... Discriminator Loss: 1.3955... Generator Loss: 0.7722
Epoch 1/1... Discriminator Loss: 1.3893... Generator Loss: 0.7739
Epoch 1/1... Discriminator Loss: 1.3887... Generator Loss: 0.7768
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.7961
Epoch 1/1... Discriminator Loss: 1.3928... Generator Loss: 0.7814
Epoch 1/1... Discriminator Loss: 1.4011... Generator Loss: 0.7784
Epoch 1/1... Discriminator Loss: 1.3842... Generator Loss: 0.7776
Epoch 1/1... Discriminator Loss: 1.3933... Generator Loss: 0.7794
Epoch 1/1... Discriminator Loss: 1.3750... Generator Loss: 0.8038
Epoch 1/1... Discriminator Loss: 1.3883... Generator Loss: 0.7693
Epoch 1/1... Discriminator Loss: 1.4148... Generator Loss: 0.7434
Epoch 1/1... Discriminator Loss: 1.4118... Generator Loss: 0.7752
Epoch 1/1... Discriminator Loss: 1.3932... Generator Loss: 0.7932
Epoch 1/1... Discriminator Loss: 1.3872... Generator Loss: 0.7773
Epoch 1/1... Discriminator Loss: 1.3881... Generator Loss: 0.7703
Epoch 1/1... Discriminator Loss: 1.3895... Generator Loss: 0.7727
Epoch 1/1... Discriminator Loss: 1.3781... Generator Loss: 0.7739
Epoch 1/1... Discriminator Loss: 1.3948... Generator Loss: 0.7623
Epoch 1/1... Discriminator Loss: 1.3849... Generator Loss: 0.7777
Epoch 1/1... Discriminator Loss: 1.4163... Generator Loss: 0.7672
Epoch 1/1... Discriminator Loss: 1.4145... Generator Loss: 0.7572
Epoch 1/1... Discriminator Loss: 1.4064... Generator Loss: 0.7777
Epoch 1/1... Discriminator Loss: 1.4135... Generator Loss: 0.7825
Epoch 1/1... Discriminator Loss: 1.4286... Generator Loss: 0.7636
Epoch 1/1... Discriminator Loss: 1.3739... Generator Loss: 0.8061
Epoch 1/1... Discriminator Loss: 1.3795... Generator Loss: 0.7909
Epoch 1/1... Discriminator Loss: 1.3714... Generator Loss: 0.7856
Epoch 1/1... Discriminator Loss: 1.3727... Generator Loss: 0.7833
Epoch 1/1... Discriminator Loss: 1.3818... Generator Loss: 0.8029
Epoch 1/1... Discriminator Loss: 1.3795... Generator Loss: 0.8051
Epoch 1/1... Discriminator Loss: 1.3821... Generator Loss: 0.7827
Epoch 1/1... Discriminator Loss: 1.3799... Generator Loss: 0.7894
Epoch 1/1... Discriminator Loss: 1.3865... Generator Loss: 0.7834
Epoch 1/1... Discriminator Loss: 1.3724... Generator Loss: 0.7934
Epoch 1/1... Discriminator Loss: 1.3911... Generator Loss: 0.7808
Epoch 1/1... Discriminator Loss: 1.4253... Generator Loss: 0.7547
Epoch 1/1... Discriminator Loss: 1.3976... Generator Loss: 0.7957
Epoch 1/1... Discriminator Loss: 1.4253... Generator Loss: 0.7774
Epoch 1/1... Discriminator Loss: 1.3976... Generator Loss: 0.7807
Epoch 1/1... Discriminator Loss: 1.3960... Generator Loss: 0.7840
Epoch 1/1... Discriminator Loss: 1.4081... Generator Loss: 0.7748
Epoch 1/1... Discriminator Loss: 1.3968... Generator Loss: 0.7711
Epoch 1/1... Discriminator Loss: 1.3925... Generator Loss: 0.7965
Epoch 1/1... Discriminator Loss: 1.3951... Generator Loss: 0.7814
Epoch 1/1... Discriminator Loss: 1.4004... Generator Loss: 0.7679
Epoch 1/1... Discriminator Loss: 1.3916... Generator Loss: 0.7890
Epoch 1/1... Discriminator Loss: 1.4029... Generator Loss: 0.7873
Epoch 1/1... Discriminator Loss: 1.3839... Generator Loss: 0.8103
Epoch 1/1... Discriminator Loss: 1.3945... Generator Loss: 0.7877
Epoch 1/1... Discriminator Loss: 1.3755... Generator Loss: 0.7875
Epoch 1/1... Discriminator Loss: 1.3925... Generator Loss: 0.7843
Epoch 1/1... Discriminator Loss: 1.3873... Generator Loss: 0.7694
Epoch 1/1... Discriminator Loss: 1.3790... Generator Loss: 0.7836
Epoch 1/1... Discriminator Loss: 1.3827... Generator Loss: 0.7904
Epoch 1/1... Discriminator Loss: 1.3963... Generator Loss: 0.7891
Epoch 1/1... Discriminator Loss: 1.3997... Generator Loss: 0.7732
Epoch 1/1... Discriminator Loss: 1.3879... Generator Loss: 0.7737
Epoch 1/1... Discriminator Loss: 1.3927... Generator Loss: 0.7871
Epoch 1/1... Discriminator Loss: 1.3797... Generator Loss: 0.7932
Epoch 1/1... Discriminator Loss: 1.3731... Generator Loss: 0.8138
Epoch 1/1... Discriminator Loss: 1.4012... Generator Loss: 0.7628
Epoch 1/1... Discriminator Loss: 1.3828... Generator Loss: 0.7825
Epoch 1/1... Discriminator Loss: 1.3900... Generator Loss: 0.7795
Epoch 1/1... Discriminator Loss: 1.3967... Generator Loss: 0.7632
Epoch 1/1... Discriminator Loss: 1.3939... Generator Loss: 0.7797
Epoch 1/1... Discriminator Loss: 1.3910... Generator Loss: 0.7885
Epoch 1/1... Discriminator Loss: 1.3776... Generator Loss: 0.7847
Epoch 1/1... Discriminator Loss: 1.3875... Generator Loss: 0.7727
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.7691
Epoch 1/1... Discriminator Loss: 1.3996... Generator Loss: 0.7815
Epoch 1/1... Discriminator Loss: 1.3908... Generator Loss: 0.7724
Epoch 1/1... Discriminator Loss: 1.3831... Generator Loss: 0.7998
Epoch 1/1... Discriminator Loss: 1.3992... Generator Loss: 0.7629
Epoch 1/1... Discriminator Loss: 1.3936... Generator Loss: 0.7835
Epoch 1/1... Discriminator Loss: 1.3947... Generator Loss: 0.7865
Epoch 1/1... Discriminator Loss: 1.3800... Generator Loss: 0.7773
Epoch 1/1... Discriminator Loss: 1.3929... Generator Loss: 0.7904
Epoch 1/1... Discriminator Loss: 1.3791... Generator Loss: 0.7889
Epoch 1/1... Discriminator Loss: 1.3838... Generator Loss: 0.7933
Epoch 1/1... Discriminator Loss: 1.3893... Generator Loss: 0.8031
Epoch 1/1... Discriminator Loss: 1.3913... Generator Loss: 0.7973
Epoch 1/1... Discriminator Loss: 1.3879... Generator Loss: 0.7846
Epoch 1/1... Discriminator Loss: 1.3862... Generator Loss: 0.7882
Epoch 1/1... Discriminator Loss: 1.3920... Generator Loss: 0.7656
Epoch 1/1... Discriminator Loss: 1.3834... Generator Loss: 0.7865
Epoch 1/1... Discriminator Loss: 1.3746... Generator Loss: 0.7899
Epoch 1/1... Discriminator Loss: 1.3861... Generator Loss: 0.7735
Epoch 1/1... Discriminator Loss: 1.3905... Generator Loss: 0.7687
Epoch 1/1... Discriminator Loss: 1.3822... Generator Loss: 0.7685

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.